Predictors of chronic kidney disease survival in type 2 diabetes: a 12-year retrospective cohort study utilizing estimated glomerular filtration rate

Predicting the course of kidney disease in individuals with both type 1 and type 2 diabetes mellitus (DM) is a significant clinical and policy challenge. In several regions, DM is now the leading cause of end-stage renal disease. The aim of this study to identify both modifiable and non-modifiable risk factors, along with clinical markers and coexisting conditions, that increase the likelihood of stage 3–5 chronic kidney disease (CKD) development in individuals with type 2 DM in the United Arab Emirates (UAE). This was a single-center retrospective cohort study based on data derived from electronic medical records of UAE patients with DM who were registered at outpatient clinics at Tawam Hospital in Al Ain, UAE, between January 2011 and December 2021. Type 2 DM patients aged ≥ 18 years who had serum HbA1c levels ≥ 6.5% were included in the study. Patients with type 1 DM, who had undergone permanent renal replacement therapy, who had under 1 year of follow-up, or who had missing or incomplete data were excluded from the study. Factors associated with diabetic patients developing stage 3–5 CKD were identified through Cox regression analysis and a fine and gray competing risk model to account for competing events that could potentially hinder the development of CKD. A total of 1003 patients were recruited for the study. The mean age of the study cohort at baseline was 70.6 ± 28.2 years. Several factors were found to increase the risk of developing stage 3–5 CKD: advancing age (HR 1.005, 95% CI 1.002–1.009, p = 0.026), a history of hypertension (HR 1.69, 95% CI 1.032–2.8, p = 0.037), a history of heart disease (HR 1.49, 95% CI 1.16–1.92, p = 0.002), elevated levels of serum creatinine (HR 1.006, 95% CI 1.002–1.010, p = 0.003), decreased levels of estimated glomerular filtration rate (eGFR) (HR 0.943, 95% CI, 0.938–0.947; p < 0.001), and the use of beta-blockers (HR 139, 95% CI 112–173, p = 0.003). Implementing preventative measures, initiating early interventions, and developing personalized care plans tailored to address specific risk factors are imperative for reducing the impact of CKD. Additionally, the unforeseen findings related to eGFR highlight the ongoing need for research to deepen our understanding of the complexities of kidney disease.


Study area
Al Ain, with a population of approximately 1.4 million, ranks as the fourth-largest city in the UAE 34 .Among its prominent institutions, Tawam Hospital stands out as a leading tertiary care center, renowned for providing specialized medical services not only to the local community but also to patients from further afield.Established in 1979, Tawam Hospital has become a key component of the Abu Dhabi Health Services Company (SEHA) Health System, reflecting its important role in the healthcare landscape of the region 35 .As a doctor-led facility licensed by the Department of Health in Abu Dhabi, Tawam Hospital boasts a team of board-certified physicians from North America and Europe, all of whom have received training in Western medical practices.This international standard of healthcare is further enhanced by the hospital's association with Johns Hopkins Medicine International, which brings clinical, administrative, and educational expertise to elevate patient care quality and safety.With 509 beds, the hospital offers a wide array of services and specialties, including, but not limited to, pain management, physical therapy, in vitro fertilization (IVF), and both adult and pediatric oncology, alongside dedicated centers for obesity care and for sleep.This extensive range of services underlines Tawam Hospital's commitment to addressing diverse healthcare needs.Tawam Hospital's vision to be a leading healthcare provider both regionally and globally is underpinned by its dedication to excellence, innovation, and community engagement.Through its comprehensive services, esteemed staff, and strategic partnerships, Tawam Hospital is poised to continue its legacy of delivering superior healthcare outcomes and contributing to the well-being of the Al Ain community and beyond.

Study population (inclusion and exclusion criteria)
The study population included type 2 DM patients registered at outpatient clinics at Tawam Hospital in Al Ain, UAE.The inclusion criteria were type 2 DM patients aged ≥ 18 years who had a serum HbA1c level ≥ 6.5%, had a diagnosis established by a physician, or were receiving medications for DM (e.g., sulfonylurea, thiazolidinedione, dipeptidyl peptidase-4 inhibitor, biguanide, or insulin).Patients with CKD who had undergone permanent renal replacement therapy (hemodialysis, peritoneal dialysis, or kidney transplant); patients with type 1 DM; patients with under 1 year of follow-up or missing or incomplete data; and patients with COVID-19, cancer, HIV, or AIDS were excluded from the study.

Sample size estimation
We determined the sample size for our cohort study using OpenEpi software and the following cohort study sample size formula: (https:// www.opene pi.com/ Sampl eSize/ SSCoh ort.htm).The sample size was determined in line with the study's primary objective-to identify the incidence of stage 3-5 CKD development in individuals with type 2 DM.We employed a two-sided test with a power of (1 − β) = 0.95 and a significance level of α = 0.05.The control-to-case ratio was set at 1. Based on an anticipated risk ratio of 3.77 36 and an assumed proportion of controls with outcome = 3.3, our calculations indicated a minimum required sample size of 314 participants.

Sampling method and participant recruitment
Convenience sampling was used to recruit patients.The patients were recruited retrospectively from EMR of UAE patients with type 2 DM who were registered at outpatient clinics at Tawam Hospital in Al Ain, UAE.
The annual follow-up data for this retrospective cohort study were collected from January 2011 to December 2021 to establish the risk factors for CKD in type 2 DM patients undergoing surveillance for the condition.
Baseline clinical variables, demographic data, and time to event (development of stage 3-5 CKD) were collected from an electronic database.We identified patients using unique reference numbers, which helped ensure that patients met the inclusion criteria, which, in turn, reduced the reporting error.The eGFR was repeatedly evaluated for each patient every 3 months, from baseline to December 2021.Additionally, follow-up laboratory tests were revised and monitored to ensure that patients fulfilled the inclusion criteria; this enhanced the quality of the collected data.A data collection form (in an Excel sheet) was designed for data collection purposes.The data collected for each patient included participant ID number and baseline covariates.Patients' characteristics were recorded at baseline.The collected data included: (1) sociodemographics, (2) detailed medical history, (3) anthropometric measurements, (4) laboratory analyses and clinical parameters, and (5) disease characteristics and medications.For detailed operational definitions of patients' characteristics, see supplementary materials.

Data quality
To ensure the integrity and quality of our data throughout this study, meticulous protocols were established.Initially, we set a follow-up duration of 11.7 years to capture a broad spectrum of CKD occurrences.We then defined precise inclusion criteria to encompass all qualified patients while minimizing the risk of excluding potential CKD cases.To further refine our cohort, we excluded individuals with less than 1 year of follow-up or who lacked baseline data, employing stringent selection standards to ensure access to complete and up-to-date medical records.This approach ensured the collection of comprehensive participant information.Routine patient monitoring facilitated the timely documentation of CKD events, effectively reducing the chances of administrative censoring and loss of follow-up.From the outset of the study until December 2021, we conducted quarterly assessments of each patient's eGFR, allowing for continuous surveillance of their condition.Additionally, we conducted in-depth analyses of patient records to identify and document any competing events that might have affected CKD progression, ensuring these were appropriately considered in our analysis.Lastly, to properly address outcomes such as cardiovascular complications, mortality, initiation of renal replacement therapy, and discontinuation of statin use, we applied a Fine and Gray competing risk model.These systematic and thorough methodologies not only enhanced the robustness and credibility of our retrospective cohort study but also assured the generation of accurate, high-quality data and precise estimates of CKD incidence.

Statistical analysis
For data entry, coding, and analysis, we used SPSS Version 26.Various procedures, including independent samples t-tests, one-way ANOVA, the Mann-Whitney U test, the Kruskal-Wallis test, and χ 2 or Fisher's exact tests for categorical data, were used to evaluate the baseline characteristics of the patients.The Shapiro-Wilk test or a visual inspection of a normal QQ plot was used to verify normality.Data missing from the dependent variable and covariate were not imputed.The observation duration, which was calculated from baseline to the last outpatient appointment or the diagnosis of stage 3-5 CKD, was expressed as years patient was at risk of developing stage 3-5 CKD.Factors linked to the development of stage 3-5 CKD in diabetic patients were determined by Cox regression analysis.A Cox-Snell residual graph, a log-log plot, and a Schoenfeld residuals global test were used to evaluate the suitability of the model.Predictor variables were analyzed using univariate Cox regression, and those with p < 0.1 were included in multivariable analysis through a stepwise backward selection process 36 .A Fine and Gray competing risk regression model assessed the connection between possible risk variables and stage 3-5 CKD 37 .This model considered competing events such as concomitant diseases, comorbidities, and stopping statin medication.In order to handle multicollinearity, variables in the Fine and Gray model were chosen using LASSO with BIC.For the most predictive covariates, the shrinkage parameter that was chosen minimized the BIC 38,39 .Statistical significance was established when p < 0.05 using R software version 3.6.3.

Ethical considerations
This study was reviewed and approved by the institutional ethical committee of Tawam Hospital in Al Ain, UAE (Ref.No.: AA/AJ/771), and by the Human Research Ethics Committee (JePEM) of Universiti Sains Malaysia.All methods were conducted in accordance with relevant guidelines and regulations.All forms were anonymous and were entered into SPSS software.Only research team members accessed the data.Data presented were grouped and did not identify the respondents individually.

Patient enrollment process
Out of the 1265 patients who met the inclusion criteria, 262 were found to be ineligible for various reasons.Among them, 122 had eGFR levels below 60 mL/min/1.73m 2 ; 15 required hemodialysis due to CKD; 8 had undergone transplantation; and 86 had incomplete data on baseline HbA1c, urea, albumin, total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio, or vitamin D. From the baseline until December 26th, 2021, we monitored the eGFR of each patient every 3 months.Unfortunately, during this period we could not obtain follow-up measurements for urea or serum creatinine (SCr) from 31 patients, which led to their exclusion due to loss of follow-up data.As a result of these considerations, a total of 1003 patients with an eGFR greater than or equal to 60 mL/min/1.73m 2 were ultimately included in this study (Fig. 1).

Demographics and baseline characteristics
Table 1 presents the demographic characteristics and comorbidities of the study patients.The mean age of the study cohort at baseline was 70.6 ± 28.2 years.Of all patients, 60% (n = 602) were female and 40% (n = 401) were male.Of the total participants, 8.2% (n = 82) were smokers and 36.9%(n = 370) had a family history of DM.The majority of the study cohort had a history of hypertension (848/1003; 84.5%), 90.6% (n = 909) had a history of dyslipidemia, and 14.4% (n = 144) had a history of ischemic heart disease.
Patients with a stage 3-5 CKD event were older at baseline, less frequently had a family history of DM, and less frequently had a history of hypertension but more frequently had a history of ischemic heart disease (Table 2).
Table 3 presents concurrent medications of the study cohort.Of the total patients, 81 (8.1%) were non-statin users, 710 (70.8%) were low to moderate intensity statin users, and 212 (21.1%) were high intensity statin users.
Table 4 illustrates the patients' medication usage based on the development of stage 3-5 CKD.Patients with stage 3-5 CKD were more frequent users of diuretics, beta-blockers, calcium channel blockers, and insulin but less frequently used ARBs and biguanides compared to patients without CKD.

Analyses of risk factors for and predictors of time to stage 3-5 CKD among diabetic patients
Table 6 presents the univariate and multivariate Cox regression analyses for the risk factors associated with the development of stage 3-5 CKD.
The results of the univariate Cox regression models showed that older age; a history of hypertension; a history of ischemic heart disease; higher levels of SBP, HbA1c, SCr, urea, and potassium; lower levels of DBP, eGFR, ALT, and albumin; and the use of diuretics, ACEIs, ARBs, beta-blockers, calcium channel blockers, insulin, and high intensity statins increased the risk of developing stage 3-5 CKD.In contrast, a lower risk of stage 3-5 CKD was associated with the use of biguanides.
Table 7 presents the results of multivariable Fine and Gray competing risk regression.Among the 39 variables we considered, the LASSO selection technique pinpointed 6 that emerged as predictors for the progression of stage 3-5 CKD in our multivariable competing risk regression model.The HRs, 95% confidence intervals (CIs), and p values associated with these variables are presented in Table 7.
The results of the Fine and Gray competing risk regression analysis were consistent with the findings of the standard multivariable Cox regression analysis.

Discussion
To knowledge, this is the first study to assess the risk factors for developing stage 3-5 CKD in patients with type 2 DM in the UAE.The outcomes of this research underscore the significance of baseline eGFR and SCr levels as important predictors of the onset of stage 3-5 CKD.Specifically, baseline eGFR has been identified as an important predictor of the development of these specific stages of the disease across both the general population and high-risk groups, inclusive of patients diagnosed with DM [40][41][42][43][44] .A reduction in eGFR below a critical threshold initiates a detrimental cycle, exacerbating renal impairment and contributing to hypertension, which subsequently accelerates the loss of nephrons 45 .
Our study also indicated that factors such as advancing age, a prior diagnosis of hypertension, and the presence of ischemic heart disease were independent risk factors for the development of stage 3-5 CKD.In a similar vein, various studies have identified age, smoking, obesity, dyslipidemia, and hypertension as independent risk factors for advancing to stage 3-5 CKD 40,[46][47][48][49][50][51][52][53] .Notably, beyond the age of 50, the lifetime risk for the onset of CKD escalates by approximately 40%, with potential further increases when additional risk factors like obesity, high blood pressure, or DM [54][55][56][57][58] are present.Furthermore, a substantial body of research has consistently affirmed a robust linkage between high blood pressure and CKD 49,50,59 .This underscores the need for comprehensive management of these risk factors within the context of DM care, aligning with findings from previous research [60][61][62] .
The utilization of beta-blockers in patients with chronic renal disease has been a topic of ongoing debate, primarily due to concerns about the potential to decrease cardiac output.Theoretically, a reduction in cardiac output could lead to diminished blood flow in the renal arteries, adversely affecting kidney perfusion 63 .
Interestingly, within our patient cohort, the use of beta-blockers was identified as a risk factor for advancing to stage 3-5 CKD.This statistical linkage might be attributed to the potential of beta-blockers to diminish cardiac output, subsequently leading to compromised renal perfusion-a condition posited to exert adverse effects on patients with CKD 64 .Furthermore, traditional beta-blockers such as propranolol, atenolol, and metoprolol have been documented to result in reduced eGFR and diminished renal blood flow.This reduction is a direct consequence of their capacity to lower cardiac output and increase peripheral vascular resistance, an effect intensified by the lack of a blockade at alpha-1 receptors 65 .
This particular finding may explain why beta-blockers were not extensively used in the current study (only 30% of the individuals in the study cohort were prescribed beta-blockers).This limited prescription rate could be attributed to the tolerability of the agents 66 .This trend aligns with other research, which has noted that only 20-30% of patients diagnosed with CKD are prescribed beta-blockers 67,68 .www.nature.com/scientificreports/Despite the concerns and limited prescription rates associated with beta-blockers in context of CKD, it is important to note that cardiovascular disease is a predominant cause of death among CKD patients.Betablockers have been shown to reduce mortality rates in patients who have experienced a myocardial infarction as well as in those with chronic systolic heart failure 63,69,70 .Considering the elevated incidence of coronary artery disease and heart failure within the CKD patient demographic, beta-blockers could potentially offer substantial benefits to this patient population.This assertion is backed by a comprehensive systematic review of eight clinical studies, which concluded that, in CKD patients with heart failure, beta-blockers significantly reduced both all-cause mortality (relative risk (RR) 0.72, CI 0.64-0.80)and cardiovascular mortality (RR 0.66, CI 0.49-0.89)compared to placebo 69 .This intricate balance between renal and cardiovascular outcomes necessitates careful consideration by clinicians, who are tasked with developing personalized treatment plans that weigh the renal implications against the cardiovascular advantages 53,56 .www.nature.com/scientificreports/ In the realm of clinical practice, the challenge of making early predictions regarding stage 3-5 CKD based on eGFR values is substantial 71 .Addressing this issue provides healthcare practitioners with valuable tool to identify patients at risk, enabling the swift implementation of lifestyle modifications, adjustments in medication, and the initiation of preventative strategies aimed at preserving renal function 72 .Engaging in such preemptive actions has the potential to improve patient care, promote favorable outcomes, and alleviate the overall strain on healthcare systems 73 .Our study underscores the challenges of accurately predicting stage 3-5 CKD using eGFR values in clinical settings.There is a critical need for more precise predictive tools to facilitate early and effective interventions.Advancing our understanding of the combined effects of various risk factors on CKD progression is essential for improving risk prediction models, thereby offering the potential to transform clinical practice by enabling the early identification and preventative management of high-risk patients.
The main strength of our study is its significant contribution to the existing literature on CKD and its particular focus on the population of the UAE.By shedding light on epidemiological patterns and identifying specific risk factors within this demographic, our research provides invaluable insights for healthcare providers in the region.This tailored approach, informed by population-specific data, is crucial for designing interventions that are aligned with the unique health profile and healthcare framework of the UAE.
Another notable strength of our research is its distinction as the first longitudinal study to assess the epidemiology of stage 3-5 CKD, alongside specific risk factors, in a population of type 2 DM patients who are nationals of the UAE.This study is further characterized by a considerable follow-up duration of 11 years.Ideally, an extended follow-up period would be advantageous, as it would facilitate a more comprehensive understanding of the long-term risk factors associated with the progression to stage 3-5 CKD.
Another merit of the research is the methodology employed for diagnosing stage 3-5 CKD, which was based on two consecutive eGFR readings < 60 mL/min/1.73m 2 , spaced ≥ 3 months apart.This approach could help account for the intra-individual variability associated with eGFR, leading to a more precise representation of renal function.In addition, the CKD-EPI equation was utilized to define the study's outcome, a method deemed more accurate than the Modification of Diet in Renal Disease Study equation, as corroborated by the majority of existing studies [74][75][76][77] .Moreover, this study utilized documented anthropometric and laboratory measurements, as opposed to relying on self-reported data, for both the predictor variables and the outcomes, thereby ensuring a higher level of data reliability.

Study Limitations
This investigation is subject to several limitations.First, the retrospective nature of the study could have introduced biases and limitations in data quality, which might have been mitigated through a prospective study design involving standardized measurements of laboratory variables and anthropometric parameters.
Second, the study did not explore certain risk factors, such as albuminuria, despite numerous studies highlighting its predictive value for the development of kidney failure 50,[78][79][80][81] .In the UAE, non-nephrologist physicians have reported that albuminuria is not routinely measured in clinical practice, with nearly 80% relying solely on eGFR as a screening tool for CKD 82 .
Third, our study's sample size was relatively modest compared to other investigations in this field.Fourth, the study's findings were derived from data collected at a single hospital, which may not be representative of the broader international context.Fifth, given the study's reliance on a retrospective review of patient records, it is possible that not all factors influencing survival probabilities were captured.

Conclusion
The current study emphasizes the necessity for a holistic strategy in the prevention, identification, and management of CKD.Healthcare professionals and policymakers should consider the complex and multifaceted nature of this disease, as well as the interrelationships between various risk factors.Implementing preventative measures, initiating early interventions, and developing personalized care plans tailored to address specific risk factors are imperative for reducing the impact of CKD.Additionally, the unforeseen findings related to eGFR highlight the ongoing need for research to deepen our understanding of the complexities of kidney disease.This study provides valuable insights into the factors that contribute to CKD risk, laying a solid foundation for future research aimed at improving strategies for the prevention and management of kidney disease.
Table 7. Multivariable Fine and Gray competing risk regression analysis model for developing stage 3-5 CKD.The predictors were scaled using z-score transformation, and HRs should be interpreted as 1 SD change in the values of the parameter.HR hazard ratio, CI confidence interval.

Figure 1 .
Figure 1.Flow diagram of the patient cohort.

Table 1 .
Demographics and comorbidities of the study cohort (N = 1003).DM diabetes mellitus.